Nonstationarity in Spatiotemporal Fisheries Models

Abstract

Many fish species occur in areas with complicated geography. Natural barriers such as islands and coastlines mean that the spatial structure of the population is unlikely to be stationary. Here I develop and fit a spatiotemporal model that accounts for nonstationarity. The stochastic partial differential equation approach is used to reduce the computational burden. A simulation study demonstrates improved abundance estimates. This improvement has the potential to improve management decisions by more accurately reflecting a stock’s spatial structure. It should also provide more trustworthy estimates of uncertainty. These combined have the potential to improve management decision in many fisheries.

Date
Aug 30, 2018 11:35 AM
Location
Vancouver, BC, Canada